• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1734-1737
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• 1997

The conventional fire detection devices are operated after a processed fire phase, which are sensing only a high density of somke level or high temperature heat. They are not so precision to detect a fire in the early phase to protect the facility form the fire. We need to develope a new high precision smoke detection system to keep expensive industrial facilities most reliably form fire. A new optical precision smoke detection system was developed. It monitors very low level density of smoke particles in the air. It is operated continously through many years without a stop or any malfunction. The developed precision smoke detection system will be installed in important industrial facilities, such as power plants, underground common tunnel, main control rooms, computer rooms etc.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 춘계학술대회 논문집
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• pp.128-132
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• 1997

The conventional fire detection devices are operated after a processed fire phase, which are sensing only a high density of smoke level or high temperature heat. They are not so precision to detect a fire in the early phase to protect the facility from the fire. We need to develope a new high precision smoke detection system to keep expensive industial facilities most reliably from fire. A new optical precision smoke detection system was developed. It monitors very low level density of smoke psrticles in the air. It is operated continuously through many years without a stop or any malfunction. The developed precision smoke detection system will be installed in important industrial facilities,such as power plants, underground common tunnel,main control rooms,computer rooms etc.

• 한국정밀공학회지
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• 제31권9호
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• pp.847-854
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• 2014

The paper presented a method of early fire detection based on the environmental characteristics inside the nacelle of wind turbine generator system(WTGS). The rising rates of the temperature and smoke density were used as the parameters for early fire detection. By considering the characteristics of temperature and smoke density of a nacelle, this method is very reliable and can minimize the possibility of a malfunction of fire detection. The performance of the method was tested through sets of experiments by using nacelle simulator.

• Journal of Advanced Marine Engineering and Technology
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• 제28권2호
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• pp.285-291
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• 2004

Early detection of an internal malfunction of machinery plays a very important part in all condition monitoring programs. Sensors to detect amplitude. velocity and acceleration are widely used in vibration detection and control. Piezoceramic materials are largely used in sensors and actuators for vibration monitoring and control due to their relatively large output from an induced strain and their arguable self powering characteristics. In this paper a cheap and yet reliable sensors/actuators were developed to detect vibration. The results show that low cost PZT can be designed for optimum detection of bearing vibration. This paper presents the experimental results of a number of piezoceramics characteristics in terms of resonant frequencies and variation of PZT constants with temperature.

• Journal of Advanced Marine Engineering and Technology
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• 제26권4호
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• pp.493-500
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• 2002

The operational data of diesel generator engine is two kinds of data. One is interactive the other is non interactive. We can find the fault information from interactive data measured for every sampling time when the changing rate, direction and status of data are investigated in comparition with those of normal status to diagnose the fault of combustion system. The various data values of combustion system for diesel engine are not proportional to load condition. The criterion to decide the level of data value is not absolute but relative to relational data. This study proposes to compose malfunction diagnosis engine using neural networks to decide that level of data value is out of normal status with the data collected from generator engine of the ship using the commercial data mining tool. This paper investigates the real ship's operational data of diesel generator engine and confirms usefulness of fault detecting through simulations for fault detecting.

• 동력기계공학회지
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• 제2권2호
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• pp.73-80
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• 1998

The identification of drilling joint dynamics which consists of drilling and structural dynamics and the on-line time series detection of malfunction process is substantial not only for the investigation of the static and dynamic characteristics but also for the analytic realization of diagnostic and control systems in drilling. Therefore, We have discussed on the comparative assessment of two recursive time series modeling algorithms that can represent the drilling operation and detect the abnormal geometric behaviors in precision roundshape machining such as turning, drilling and boring in precision diemaking. For this purpose, simulation and experimental work were performed to show the malfunctional behaviors for drilling operation. For this purpose, a new two recursive approach (Recursive Extended Instrument Variable Method : REIVM, Recursive Least Square Method : RLSM) may be adopted for the on-line system identification and monitoring of a malfunction behavior of drilling process, such as chipping, wear, chatter and hole lobe waviness.

• 한국마린엔지니어링학회:학술대회논문집
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• 한국마린엔지니어링학회 2002년도 춘계학술대회논문집
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• pp.245-250
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• 2002

The operational data of diesel generator engine is two kind of discrete signal and analog signal. We can find the fault information from analog data measured for every sampling time if it is invested the changing rate or direction of data. This paper propose the Malfunction Diagnosis Engine(MDE) using the commercial data mining tool and show the data Process and fault finding method with the data collected from generator engine of the ship.

• 한국표면공학회지
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• 제48권4호
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• pp.179-184
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• 2015

Quadrupole Mass Spectrometers (QMS) is a very useful tool in vacuum process diagnosis. Tungsten filament based ion sources are vulnerable to contamination from process gas monitoring. Common symptoms of quadrupole mass spectrometer malfunction is appearance of unwanted contaminant mass peaks or no detection of any ion peaks. We disassembled used quadrupole mass spectrometer and found out black insulating deposits on inside of ion source parts. Five steps of cleaning procedure were applied and almost full restoration of functions were confirmed in two types of closed ion source quadrupole mass spectrometer. By using a numerical modeling (CFD-ACE+) technique, the electric potential profile of ion source with/without insulating deposit was calculated and showed the possibility of quadrupole mass spectrometer malfunction by the deterioration of designed potential profile inside the ion source.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 하계종합학술대회논문집
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• pp.235-238
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• 1998

This paper presents the detection of internal combustion engine's multiple misfire. The primary cause of air pollution by vehicles is imperfect conbustion of fuel. The CARB(California Air Resources Board) have imposed regulations for the detection of misfiring in automotive engines. The OBD-II regulations requir that misfire should be monitored by the diagnostic system, and that the goal of OBD-II is to alert the driver to the presence of a malfunction of the emission control system. Present invention based upon measurements of engine roughness as derived from crankshaft angular velocity measurements with special signal processing method. Crankshaft angular velocity signals are processed by walsh-fourier transform. Experimental work confims that it's possible to apply walsh-fourier transform for the detection of multiple misfires in no-load idle and road testing.

• 한국측량학회지
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• 제34권6호
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• pp.619-627
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• 2016

Cells of a PV (photovoltaic) module can suffer defects due to various causes resulting in a loss of power output. As a malfunctioning cell has a higher temperature than adjacent normal cells, it can be easily detected with a thermal infrared sensor. A conventional method of PV cell inspection is to use a hand-held infrared sensor for visual inspection. The main disadvantages of this method, when applied to a large-scale PV power plant, are that it is time-consuming and costly. This paper presents an algorithm for automatically detecting defective PV panels using images captured with a thermal imaging camera from an UAV (unmanned aerial vehicle). The proposed algorithm uses statistical analysis of thermal intensity (surface temperature) characteristics of each PV module to verify the mean intensity and standard deviation of each panel as parameters for fault diagnosis. One of the characteristics of thermal infrared imaging is that the larger the distance between sensor and target, the lower the measured temperature of the object. Consequently, a global detection rule using the mean intensity of all panels in the fault detection algorithm is not applicable. Therefore, a local detection rule was applied to automatically detect defective panels using the mean intensity and standard deviation range of each panel by array. The performance of the proposed algorithm was tested on three sample images; this verified a detection accuracy of defective panels of 97% or higher. In addition, as the proposed algorithm can adjust the range of threshold values for judging malfunction at the array level, the local detection rule is considered better suited for highly sensitive fault detection compared to a global detection rule. In this study, we used a panel area extraction method that we previously developed; fault detection accuracy would be improved if panel area extraction from images was more precise. Furthermore, the proposed algorithm contributes to the development of a maintenance and repair system for large-scale PV power plants, in combination with a geo-referencing algorithm for accurate determination of panel locations using sensor-based orientation parameters and photogrammetry from ground control points.